Files in This Item:
| File | Format | ||
|---|---|---|---|
| b1267444.mp4 | Streaming Video | View/Open |
| Title: | Dimensional Analysis for Big Data |
| Originating Office: | IAS |
| Speaker: | Lin, Dennis |
| Issue Date: | 19-Dec-2013 |
| Event Date: | 19-Dec-2013 |
| Group/Series/Folder: | Record Group 8.15 - Institute for Advanced Study Series 3 - Audio-visual Materials |
| Location: | 8.15:3 EF |
| Notes: | HKUST International Forum on Probability and Statistics. Talk no. 9. Title from slide title. The Second HKUST International Forum on Probability and Statistics (2013), held 19 December, 2013, at the Hong Kong University of Science and Technology. Co-sponsored by the HKUST Jockey Club Institute for Advanced Study and the Center for Statistical Science. Abstract: The ability to parse information, faster and deeper, is allowing researchers to understand the world in a way they could only dream about before. In this talk (first portion), the common understanding about BIG data will be discussed. Its challenges and impacts to Statistics will be addressed. In particular, the speaker is interested in what types of Statistics are needed for BIG data era. On the other hand, Dimensional Analysis (DA) is a fundamental method in the engineering and physical sciences for analytically reducing the number of experimental variables prior to the experimentation. The method is of great generality. In this talk (second portion), an overview/introduction of DA will be given. Some initial ideas on using DA for BIG data will be discussed. Future research issues will be proposed. Duration: 41 min. |
| Appears in Series: | 8.15:3 - Audio-visual Materials Videos for Public -- Distinguished Lectures |